Decision Support for Group-Based Configuration using Recommender Systems

A group of people with diferent personal preferences wants to fnd a solution to a problem with high variability. Making decisions in the group comes with problems as a lack of communication leads to worse decision outcomes. Group dynamics and biases can lead to suboptimal decisions. Generally group decisions are complex and often the process that yields the

decision result is unstructured, thereby not providing any reproducibility of the success. Groups have different power structures and usually individuals have diferent interests. Moreover finding solutions is a rather complex task and group decisions can sufer intransparency. To support groups in their decision making product confguration can be used. It allows to accurately map constraints and dependencies in complex problems and to map the solution space. Using a group recommender a group is supported in their confguration decisions. The goal is to show that these approaches can help a group with the confguration task presented by the usage of a configurator and to better process individual preferences than a human can. The benefts of this approach are, that the need for a group to communicate directly is reduced.
Each user gives their own preferences and the group will get a recommendation based on that. This allows to reduce problems arising in groups decisions like lack of communication and bias in groups. Additionally this shows the viability of combining group recommendations and configuration approaches.